The applications of neural network filter to estimation of oil spoil in sea

被引：0

作者：

Tong Yuming ^{[2
]}

Xu Dijian ^{[1
]}

Shi Jinliang ^{[1
]}

Zeng Jiankui ^{[1
]}

机构：

[1] Chongqing Univ Sci & Technol, Chongqing, Peoples R China

[2] Chongqing Normal Univ, Chongqing, Peoples R China

来源：

ENGINEERING SOLUTIONS FOR MANUFACTURING PROCESSES IV, PTS 1 AND 2 | 2014年 / 889-890卷

关键词：

Artificial Neural Network (ANN); Oil spoil; Maximum Likelihood; Target detection; Parameter estimation; ARRIVAL; LOCATION;

D O I：

10.4028/www.scientific.net/AMR.889-890.1625

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The oil spoil detection is an important problem in many applications such as oil exploration and transportation. But in some application such as sea, this task is very difficult because of the strong clutter. Many algorithms have been proposed for this problem. The Maximum Likelihood (ML) is one of those good solutions. This paper describes an application of neural network (NN) for obtaining the global optimal solution of finding oil spoil. It improves the estimation accuracy. The computation complexity is modest.

引用

页码：1625 / +

页数：2

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